Theoretical analysis indicates that iterative learning control algorithm is robust if initial shift and System parameter disturbance within limited bound.

理论分析表明，当系统状态初值漂移和系统参数扰动在一定范围内，迭代学习控制算法关于是鲁棒的。

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Following theoretical analysis, an efficent heuristic algorithm combined with the branch-and-bound algorithm was developed.

并通过理论分析提出一种启发式与分枝定界相结合的算法。

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